GPT-5 Nano vs Grok 3 Mini

Across our 12 internal benchmarks, GPT-5 Nano and Grok 3 Mini each win five tests, with two ties — as close a split as you can get.

GPT-5 Nano's wins:

• Structured output (5 vs 4): GPT-5 Nano scores 5/5, tied for 1st among 54 models with 24 others. Grok 3 Mini scores 4, ranking 26th. For JSON schema compliance and format adherence in production pipelines, GPT-5 Nano is the safer bet.
• Strategic analysis (4 vs 3): GPT-5 Nano ranks 27th of 54 with a score of 4; Grok 3 Mini scores 3, ranking 36th. The gap here is meaningful — nuanced tradeoff reasoning with real numbers is a full point higher on our scale.
• Safety calibration (4 vs 2): This is the largest gap in the entire comparison. GPT-5 Nano scores 4 and ranks 6th of 55; Grok 3 Mini scores 2, ranking 12th. Safety calibration — correctly refusing harmful requests while permitting legitimate ones — sits at the 75th percentile at a score of 2 across all models, meaning Grok 3 Mini is at the median while GPT-5 Nano is well above it. For consumer-facing or regulated applications, this matters.
• Agentic planning (4 vs 3): GPT-5 Nano ranks 16th of 54; Grok 3 Mini ranks 42nd. A significant ranking gap for goal decomposition and failure recovery — relevant for any multi-step autonomous workflow.
• Multilingual (5 vs 4): Both are competitive, but GPT-5 Nano ties for 1st among 55 models while Grok 3 Mini ranks 36th.

Grok 3 Mini's wins:

• Tool calling (5 vs 4): Grok 3 Mini ties for 1st among 54 models with 16 others; GPT-5 Nano ranks 18th. For function selection, argument accuracy, and sequencing in agentic pipelines, Grok 3 Mini has a clear edge.
• Faithfulness (5 vs 4): Grok 3 Mini ties for 1st among 55 models with 32 others. GPT-5 Nano ranks 34th. Sticking to source material without hallucinating is Grok 3 Mini's strongest area — critical for RAG and summarization tasks.
• Classification (4 vs 3): Grok 3 Mini ties for 1st among 53 models; GPT-5 Nano ranks 31st. Accurate categorization and routing is a meaningful gap.
• Constrained rewriting (4 vs 3): Grok 3 Mini ranks 6th of 53; GPT-5 Nano ranks 31st. Compression within hard character limits favors Grok 3 Mini.
• Persona consistency (5 vs 4): Grok 3 Mini ties for 1st among 53 models; GPT-5 Nano ranks 38th. Maintaining character and resisting injection is notably stronger in Grok 3 Mini.

Ties:

• Creative problem solving (3 vs 3): Both rank 30th of 54 — below median for the field.
• Long context (5 vs 5): Both tie for 1st among 55 models.

External benchmarks (Epoch AI): GPT-5 Nano scores 95.2% on MATH Level 5 (rank 7 of 14 models tested, sole holder of that score) and 81.1% on AIME 2025 (rank 14 of 23). These place it in the upper half of math-capable models in our dataset. Grok 3 Mini has no external benchmark scores in the payload. The median MATH Level 5 score across models we track is 94.15% and the median AIME 2025 score is 83.9%, putting GPT-5 Nano slightly above median on MATH and slightly below median on AIME among tested models.

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens. Grok 3 Mini costs $0.30 per million input tokens and $0.50 per million output tokens. The input cost gap is the dominant factor for most workloads. At 1M input tokens/month, GPT-5 Nano costs $0.05 vs $0.30 — a $0.25 difference that is negligible. At 10M tokens/month, that gap grows to $2.50. At 100M tokens/month, you're paying $5 vs $30 on input alone — a $25/month difference that starts to matter for cost-sensitive pipelines. Output costs are close: $40 vs $50 per 100M output tokens, a $10 gap. For any workload that is input-heavy — long-document processing, RAG pipelines, batch classification — GPT-5 Nano's input pricing is a significant structural advantage. For output-heavy workloads like generation or chat, the gap narrows considerably. Developers building at scale should strongly weight GPT-5 Nano's input price unless their specific task (tool calling, faithfulness, classification) clearly favors Grok 3 Mini.

Choose GPT-5 Nano if: you need structured output reliability (5/5, tied for 1st), agentic planning quality (4/5, rank 16/54), strong safety calibration for consumer-facing apps (4/5 vs Grok 3 Mini's 2/5), multilingual support, or you're running high input-token volumes where its $0.05/MTok input price vs $0.30/MTok for Grok 3 Mini creates real cost savings. GPT-5 Nano also supports image and file inputs, which Grok 3 Mini does not per the payload. Its 400K context window dwarfs Grok 3 Mini's 131K, making it the only viable option for very long document workflows.

Choose Grok 3 Mini if: your workload centers on tool calling (5/5, tied for 1st among 54 models), faithfulness to source material (5/5, tied for 1st), classification and routing tasks (4/5, tied for 1st), constrained rewriting, or persona-consistent chat applications. Grok 3 Mini also exposes raw thinking traces and supports logprobs and top_p parameters — useful for developers who need more control over generation. If your pipeline is output-heavy and you don't need the 400K context window, the output price difference ($0.50 vs $0.40/MTok) is small enough that Grok 3 Mini's task advantages can justify the modest premium.